Natural Deduction with Propositional Logic
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Chapter 5: Methods of Proof for Boolean Logic
Chapter 5: Methods of Proof for Boolean Logic § 5.1 Valid inference steps Conjunction elimination Sometimes called simplification. From a conjunction, infer any of the conjuncts. • From P ∧ Q, infer P (or infer Q). Conjunction introduction Sometimes called conjunction. From a pair of sentences, infer their conjunction. • From P and Q, infer P ∧ Q. § 5.2 Proof by cases This is another valid inference step (it will form the rule of disjunction elimination in our formal deductive system and in Fitch), but it is also a powerful proof strategy. In a proof by cases, one begins with a disjunction (as a premise, or as an intermediate conclusion already proved). One then shows that a certain consequence may be deduced from each of the disjuncts taken separately. One concludes that that same sentence is a consequence of the entire disjunction. • From P ∨ Q, and from the fact that S follows from P and S also follows from Q, infer S. The general proof strategy looks like this: if you have a disjunction, then you know that at least one of the disjuncts is true—you just don’t know which one. So you consider the individual “cases” (i.e., disjuncts), one at a time. You assume the first disjunct, and then derive your conclusion from it. You repeat this process for each disjunct. So it doesn’t matter which disjunct is true—you get the same conclusion in any case. Hence you may infer that it follows from the entire disjunction. In practice, this method of proof requires the use of “subproofs”—we will take these up in the next chapter when we look at formal proofs. -
Notes on Proof Theory
Notes on Proof Theory Master 1 “Informatique”, Univ. Paris 13 Master 2 “Logique Mathématique et Fondements de l’Informatique”, Univ. Paris 7 Damiano Mazza November 2016 1Last edit: March 29, 2021 Contents 1 Propositional Classical Logic 5 1.1 Formulas and truth semantics . 5 1.2 Atomic negation . 8 2 Sequent Calculus 10 2.1 Two-sided formulation . 10 2.2 One-sided formulation . 13 3 First-order Quantification 16 3.1 Formulas and truth semantics . 16 3.2 Sequent calculus . 19 3.3 Ultrafilters . 21 4 Completeness 24 4.1 Exhaustive search . 25 4.2 The completeness proof . 30 5 Undecidability and Incompleteness 33 5.1 Informal computability . 33 5.2 Incompleteness: a road map . 35 5.3 Logical theories . 38 5.4 Arithmetical theories . 40 5.5 The incompleteness theorems . 44 6 Cut Elimination 47 7 Intuitionistic Logic 53 7.1 Sequent calculus . 55 7.2 The relationship between intuitionistic and classical logic . 60 7.3 Minimal logic . 65 8 Natural Deduction 67 8.1 Sequent presentation . 68 8.2 Natural deduction and sequent calculus . 70 8.3 Proof tree presentation . 73 8.3.1 Minimal natural deduction . 73 8.3.2 Intuitionistic natural deduction . 75 1 8.3.3 Classical natural deduction . 75 8.4 Normalization (cut-elimination in natural deduction) . 76 9 The Curry-Howard Correspondence 80 9.1 The simply typed l-calculus . 80 9.2 Product and sum types . 81 10 System F 83 10.1 Intuitionistic second-order propositional logic . 83 10.2 Polymorphic types . 84 10.3 Programming in system F ...................... 85 10.3.1 Free structures . -
Relevant and Substructural Logics
Relevant and Substructural Logics GREG RESTALL∗ PHILOSOPHY DEPARTMENT, MACQUARIE UNIVERSITY [email protected] June 23, 2001 http://www.phil.mq.edu.au/staff/grestall/ Abstract: This is a history of relevant and substructural logics, written for the Hand- book of the History and Philosophy of Logic, edited by Dov Gabbay and John Woods.1 1 Introduction Logics tend to be viewed of in one of two ways — with an eye to proofs, or with an eye to models.2 Relevant and substructural logics are no different: you can focus on notions of proof, inference rules and structural features of deduction in these logics, or you can focus on interpretations of the language in other structures. This essay is structured around the bifurcation between proofs and mod- els: The first section discusses Proof Theory of relevant and substructural log- ics, and the second covers the Model Theory of these logics. This order is a natural one for a history of relevant and substructural logics, because much of the initial work — especially in the Anderson–Belnap tradition of relevant logics — started by developing proof theory. The model theory of relevant logic came some time later. As we will see, Dunn's algebraic models [76, 77] Urquhart's operational semantics [267, 268] and Routley and Meyer's rela- tional semantics [239, 240, 241] arrived decades after the initial burst of ac- tivity from Alan Anderson and Nuel Belnap. The same goes for work on the Lambek calculus: although inspired by a very particular application in lin- guistic typing, it was developed first proof-theoretically, and only later did model theory come to the fore. -
Qvp) P :: ~~Pp :: (Pvp) ~(P → Q
TEN BASIC RULES OF INFERENCE Negation Introduction (~I – indirect proof IP) Disjunction Introduction (vI – addition ADD) Assume p p Get q & ~q ˫ p v q ˫ ~p Disjunction Elimination (vE – version of CD) Negation Elimination (~E – version of DN) p v q ~~p → p p → r Conditional Introduction (→I – conditional proof CP) q → r Assume p ˫ r Get q Biconditional Introduction (↔I – version of ME) ˫ p → q p → q Conditional Elimination (→E – modus ponens MP) q → p p → q ˫ p ↔ q p Biconditional Elimination (↔E – version of ME) ˫ q p ↔ q Conjunction Introduction (&I – conjunction CONJ) ˫ p → q p or q ˫ q → p ˫ p & q Conjunction Elimination (&E – simplification SIMP) p & q ˫ p IMPORTANT DERIVED RULES OF INFERENCE Modus Tollens (MT) Constructive Dilemma (CD) p → q p v q ~q p → r ˫ ~P q → s Hypothetical Syllogism (HS) ˫ r v s p → q Repeat (RE) q → r p ˫ p → r ˫ p Disjunctive Syllogism (DS) Contradiction (CON) p v q p ~p ~p ˫ q ˫ Any wff Absorption (ABS) Theorem Introduction (TI) p → q Introduce any tautology, e.g., ~(P & ~P) ˫ p → (p & q) EQUIVALENCES De Morgan’s Law (DM) (p → q) :: (~q→~p) ~(p & q) :: (~p v ~q) Material implication (MI) ~(p v q) :: (~p & ~q) (p → q) :: (~p v q) Commutation (COM) Material Equivalence (ME) (p v q) :: (q v p) (p ↔ q) :: [(p & q ) v (~p & ~q)] (p & q) :: (q & p) (p ↔ q) :: [(p → q ) & (q → p)] Association (ASSOC) Exportation (EXP) [p v (q v r)] :: [(p v q) v r] [(p & q) → r] :: [p → (q → r)] [p & (q & r)] :: [(p & q) & r] Tautology (TAUT) Distribution (DIST) p :: (p & p) [p & (q v r)] :: [(p & q) v (p & r)] p :: (p v p) [p v (q & r)] :: [(p v q) & (p v r)] Conditional-Biconditional Refutation Tree Rules Double Negation (DN) ~(p → q) :: (p & ~q) p :: ~~p ~(p ↔ q) :: [(p & ~q) v (~p & q)] Transposition (TRANS) CATEGORICAL SYLLOGISM RULES (e.g., Ǝx(Fx) / ˫ Fy). -
Logical Verification Course Notes
Logical Verification Course Notes Femke van Raamsdonk [email protected] Vrije Universiteit Amsterdam autumn 2008 Contents 1 1st-order propositional logic 3 1.1 Formulas . 3 1.2 Natural deduction for intuitionistic logic . 4 1.3 Detours in minimal logic . 10 1.4 From intuitionistic to classical logic . 12 1.5 1st-order propositional logic in Coq . 14 2 Simply typed λ-calculus 25 2.1 Types . 25 2.2 Terms . 26 2.3 Substitution . 28 2.4 Beta-reduction . 30 2.5 Curry-Howard-De Bruijn isomorphism . 32 2.6 Coq . 38 3 Inductive types 41 3.1 Expressivity . 41 3.2 Universes of Coq . 44 3.3 Inductive types . 45 3.4 Coq . 48 3.5 Inversion . 50 4 1st-order predicate logic 53 4.1 Terms and formulas . 53 4.2 Natural deduction . 56 4.2.1 Intuitionistic logic . 56 4.2.2 Minimal logic . 60 4.3 Coq . 62 5 Program extraction 67 5.1 Program specification . 67 5.2 Proof of existence . 68 5.3 Program extraction . 68 5.4 Insertion sort . 68 i 1 5.5 Coq . 69 6 λ-calculus with dependent types 71 6.1 Dependent types: introduction . 71 6.2 λP ................................... 75 6.3 Predicate logic in λP ......................... 79 7 Second-order propositional logic 83 7.1 Formulas . 83 7.2 Intuitionistic logic . 85 7.3 Minimal logic . 88 7.4 Classical logic . 90 8 Polymorphic λ-calculus 93 8.1 Polymorphic types: introduction . 93 8.2 λ2 ................................... 94 8.3 Properties of λ2............................ 98 8.4 Expressiveness of λ2........................ -
Propositional Team Logics
Propositional Team Logics✩ Fan Yanga,1,∗, Jouko V¨a¨an¨anenb,2 aDepartment of Values, Technology and Innovation, Delft University of Technology, Jaffalaan 5, 2628 BX Delft, The Netherlands bDepartment of Mathematics and Statistics, Gustaf H¨allstr¨omin katu 2b, PL 68, FIN-00014 University of Helsinki, Finland and University of Amsterdam, The Netherlands Abstract We consider team semantics for propositional logic, continuing[34]. In team semantics the truth of a propositional formula is considered in a set of valuations, called a team, rather than in an individual valuation. This offers the possibility to give meaning to concepts such as dependence, independence and inclusion. We associate with every formula φ based on finitely many propositional variables the set JφK of teams that satisfy φ. We define a full propositional team logic in which every set of teams is definable as JφK for suitable φ. This requires going beyond the logical operations of classical propositional logic. We exhibit a hierarchy of logics between the smallest, viz. classical propositional logic, and the full propositional team logic. We characterize these different logics in several ways: first syntactically by their logical operations, and then semantically by the kind of sets of teams they are capable of defining. In several important cases we are able to find complete axiomatizations for these logics. Keywords: propositional team logics, team semantics, dependence logic, non-classical logic 2010 MSC: 03B60 1. Introduction In classical propositional logic the propositional atoms, say p1,...,pn, are given a truth value 1 or 0 by what is called a valuation and then any propositional formula φ can be associated with the set |φ| of valuations giving φ the value 1. -
Inversion by Definitional Reflection and the Admissibility of Logical Rules
THE REVIEW OF SYMBOLIC LOGIC Volume 2, Number 3, September 2009 INVERSION BY DEFINITIONAL REFLECTION AND THE ADMISSIBILITY OF LOGICAL RULES WAGNER DE CAMPOS SANZ Faculdade de Filosofia, Universidade Federal de Goias´ THOMAS PIECHA Wilhelm-Schickard-Institut, Universitat¨ Tubingen¨ Abstract. The inversion principle for logical rules expresses a relationship between introduction and elimination rules for logical constants. Hallnas¨ & Schroeder-Heister (1990, 1991) proposed the principle of definitional reflection, which embodies basic ideas of inversion in the more general context of clausal definitions. For the context of admissibility statements, this has been further elaborated by Schroeder-Heister (2007). Using the framework of definitional reflection and its admis- sibility interpretation, we show that, in the sequent calculus of minimal propositional logic, the left introduction rules are admissible when the right introduction rules are taken as the definitions of the logical constants and vice versa. This generalizes the well-known relationship between introduction and elimination rules in natural deduction to the framework of the sequent calculus. §1. Inversion principle. The idea of inverting logical rules can be found in a well- known remark by Gentzen: “The introductions are so to say the ‘definitions’ of the sym- bols concerned, and the eliminations are ultimately only consequences hereof, what can approximately be expressed as follows: In eliminating a symbol, the formula concerned – of which the outermost symbol is in question – may only ‘be used as that what it means on the ground of the introduction of that symbol’.”1 The inversion principle itself was formulated by Lorenzen (1955) in the general context of rule-based systems and is thus not restricted to logical rules. -
Accepting a Logic, Accepting a Theory
1 To appear in Romina Padró and Yale Weiss (eds.), Saul Kripke on Modal Logic. New York: Springer. Accepting a Logic, Accepting a Theory Timothy Williamson Abstract: This chapter responds to Saul Kripke’s critique of the idea of adopting an alternative logic. It defends an anti-exceptionalist view of logic, on which coming to accept a new logic is a special case of coming to accept a new scientific theory. The approach is illustrated in detail by debates on quantified modal logic. A distinction between folk logic and scientific logic is modelled on the distinction between folk physics and scientific physics. The importance of not confusing logic with metalogic in applying this distinction is emphasized. Defeasible inferential dispositions are shown to play a major role in theory acceptance in logic and mathematics as well as in natural and social science. Like beliefs, such dispositions are malleable in response to evidence, though not simply at will. Consideration is given to the Quinean objection that accepting an alternative logic involves changing the subject rather than denying the doctrine. The objection is shown to depend on neglect of the social dimension of meaning determination, akin to the descriptivism about proper names and natural kind terms criticized by Kripke and Putnam. Normal standards of interpretation indicate that disputes between classical and non-classical logicians are genuine disagreements. Keywords: Modal logic, intuitionistic logic, alternative logics, Kripke, Quine, Dummett, Putnam Author affiliation: Oxford University, U.K. Email: [email protected] 2 1. Introduction I first encountered Saul Kripke in my first term as an undergraduate at Oxford University, studying mathematics and philosophy, when he gave the 1973 John Locke Lectures (later published as Kripke 2013). -
A Sequent System for LP
A Sequent System for LP Gladys Palau1 , Carlos A. Oller1 1 Facultad de Filosofía y Letras, Universidad de Buenos Aires Facultad de Humanidades y Ciencias de la Educación, Universidad Nacional de La Plata [email protected] ; [email protected] Abstract. This paper presents a Gentzen-type sequent system for Priest s three- valued paraconsistent logic LP. This sequent system is not canonical because it introduces non-standard axioms. Furthermore, the rules for the conditional and negation connectives are not the classical ones. Some philosophical consequences of this type of sequent presentation for many-valued logics are discussed. 1 Introduction This paper introduces a sequent system for Priest s many-valued and paraconsistent logic LP (Logic of Paradox)[6]. Priest presents this logic to deal with paradoxes, vague contexts and the alleged existence of true contradictions or dialetheias. A logic is paraconsistent if and only if its consequence relation is paraconsistent, and a consequence relation is paraconsistent if and only if it is not explosive. A consequence relation ├ is explosive if and only if, for any formulas A and B, {A, ¬A} ├ B (ECQ). In addition, Priest's logic LP is a three-valued system in which both a formula as its negation can receive a designated truth value. In his 1979 paper and in [7 ], [ 8 ] and [ 9 ] Priest offers a semantic characterization of LP. He also offers a natural deduction formulation of LP in [9]. Anthony Bloesch provides in [3] a formulation of LP as a system of signed tableaux and Tony Roy offers in [10] another presentation of LP as a natural deduction system. -
Propositional Logic
Propositional logic Readings: Sections 1.1 and 1.2 of Huth and Ryan. In this module, we will consider propositional logic, which will look familiar to you from Math 135 and CS 251. The difference here is that we first define a formal proof system and practice its use before talking about a semantic interpretation (which will also be familiar) and showing that these two notions coincide. 1 Declarative sentences (1.1) A proposition or declarative sentence is one that can, in principle, be argued as being true or false. Examples: “My car is green” or “Susan was born in Canada”. Many sentences are not declarative, such as “Help!”, “What time is it?”, or “Get me something to eat.” The declarative sentences above are atomic; they cannot be decomposed further. A sentence like “My car is green AND you do not have a car” is a compound sentence or compositional sentence. 2 To clarify the manipulations we perform in logical proofs, we will represent declarative sentences symbolically by atoms such as p, q, r. (We avoid t, f , T , F for reasons which will become evident.) Compositional sentences will be represented by formulas, which combine atoms with connectives. Formulas are intended to symbolically represent statements in the type of mathematical or logical reasoning we have done in the past. Our standard set of connectives will be , , , and . (In Math : ^ _ ! 135, you also used , which we will not use.) Soon, we will $ describe the set of formulas as a formal language; for the time being, we use an informal description. -
Isabelle for Philosophers∗
Isabelle for Philosophers∗ Ben Blumson September 20, 2019 It is unworthy of excellent men to lose hours like slaves in the labour of calculation which could safely be relegated to anyone else if machines were used. Liebniz [11] p. 181. This is an introduction to the Isabelle proof assistant aimed at philosophers and students of philosophy.1 1 Propositional Logic Imagine you are caught in an air raid in the Second World War. You might reason as follows: Either I will be killed in this raid or I will not be killed. Suppose that I will. Then even if I take precautions, I will be killed, so any precautions I take will be ineffective. But suppose I am not going to be killed. Then I won't be killed even if I neglect all precautions; so on this assumption, no precautions ∗This draft is based on notes for students in my paradoxes and honours metaphysics classes { I'm grateful to the students for their help, especially Mark Goh, Zhang Jiang, Kee Wei Loo and Joshua Thong. I've also benefitted from discussion or correspondence on these issues with Zach Barnett, Sam Baron, David Braddon-Mitchell, Olivier Danvy, Paul Oppenheimer, Bruno Woltzenlogel Paleo, Michael Pelczar, David Ripley, Divyanshu Sharma, Manikaran Singh, Neil Sinhababu and Weng Hong Tang. 1I found a very useful introduction to be Nipkow [8]. Another still helpful, though unfortunately dated, introduction is Grechuk [6]. A person wishing to know how Isabelle works might first consult Paulson [9]. For the software itself and comprehensive docu- mentation, see https://isabelle.in.tum.de/. -
List of Rules of Inference 1 List of Rules of Inference
List of rules of inference 1 List of rules of inference This is a list of rules of inference, logical laws that relate to mathematical formulae. Introduction Rules of inference are syntactical transform rules which one can use to infer a conclusion from a premise to create an argument. A set of rules can be used to infer any valid conclusion if it is complete, while never inferring an invalid conclusion, if it is sound. A sound and complete set of rules need not include every rule in the following list, as many of the rules are redundant, and can be proven with the other rules. Discharge rules permit inference from a subderivation based on a temporary assumption. Below, the notation indicates such a subderivation from the temporary assumption to . Rules for classical sentential calculus Sentential calculus is also known as propositional calculus. Rules for negations Reductio ad absurdum (or Negation Introduction) Reductio ad absurdum (related to the law of excluded middle) Noncontradiction (or Negation Elimination) Double negation elimination Double negation introduction List of rules of inference 2 Rules for conditionals Deduction theorem (or Conditional Introduction) Modus ponens (or Conditional Elimination) Modus tollens Rules for conjunctions Adjunction (or Conjunction Introduction) Simplification (or Conjunction Elimination) Rules for disjunctions Addition (or Disjunction Introduction) Separation of Cases (or Disjunction Elimination) Disjunctive syllogism List of rules of inference 3 Rules for biconditionals Biconditional introduction Biconditional Elimination Rules of classical predicate calculus In the following rules, is exactly like except for having the term everywhere has the free variable . Universal Introduction (or Universal Generalization) Restriction 1: does not occur in .